Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods or our paper for further explanation).

Using data available up to the: 2020-06-19

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-06-09) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-06-09 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-09 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-09 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-09 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-09 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-06-09)

Table 1: Latest estimates (as of the 2020-06-09) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 708 (645 – 773) Likely increasing 1 (1 – 1.1) 78 (28 – -100)
Albania 60 (44 – 73) Increasing 1.3 (1.1 – 1.5) 9.8 (5.4 – 48)
Algeria 120 (101 – 141) Unsure 1 (0.9 – 1.2) 55 (14 – -29)
Andorra 5 (0 – 14) Unsure 1.4 (0 – 2.8) 27 (1.3 – -1.6)
Argentina 1237 (1149 – 1308) Increasing 1.1 (1 – 1.2) 33 (20 – 92)
Armenia 592 (526 – 645) Increasing 1.1 (1 – 1.2) 34 (18 – 360)
Australia 18 (9 – 25) Likely increasing 1.4 (0.9 – 1.8) 7.4 (3.4 – -48)
Austria 29 (18 – 38) Unsure 1 (0.8 – 1.3) -1100 (9.7 – -9.3)
Azerbaijan 368 (328 – 408) Increasing 1.1 (1 – 1.2) 41 (18 – -220)
Bahrain 509 (461 – 558) Unsure 1 (1 – 1.1) 1200 (39 – -42)
Bangladesh 3629 (3347 – 3917) Increasing 1.1 (1.1 – 1.2) 23 (19 – 31)
Belarus 737 (674 – 798) Likely decreasing 1 (0.9 – 1) -85 (110 – -30)
Belgium 100 (81 – 116) Likely decreasing 0.9 (0.8 – 1) -33 (45 – -12)
Benin 39 (26 – 52) Increasing 1.4 (1 – 1.7) 7.7 (4.2 – 41)
Bolivia 803 (729 – 869) Increasing 1.2 (1.1 – 1.2) 16 (12 – 26)
Bosnia and Herzegovina 54 (38 – 68) Likely increasing 1.2 (0.9 – 1.4) 17 (7 – -42)
Brazil 27262 (25549 – 28956) Increasing 1 (1 – 1.1) 64 (45 – 110)
Bulgaria 89 (71 – 104) Likely increasing 1.2 (1 – 1.3) 22 (9.2 – -61)
Cameroon 234 (200 – 269) Unsure 1 (0.9 – 1.1) -40 (75 – -15)
Canada 408 (363 – 447) Decreasing 0.9 (0.8 – 1) -23 (-82 – -14)
Central African Republic 90 (68 – 109) Unsure 1 (0.9 – 1.2) -91 (18 – -13)
Chad 5 (0 – 10) Unsure 1 (0.2 – 1.9) 170 (2.4 – -2.5)
Chile 10442 (9105 – 11735) Increasing 1.3 (1.2 – 1.4) 9 (7.9 – 10)
China 40 (28 – 52) Increasing 1.6 (1.2 – 2) 5.2 (3.2 – 13)
Colombia 2255 (2041 – 2486) Increasing 1.2 (1.1 – 1.3) 13 (11 – 17)
Congo 27 (17 – 35) Likely increasing 1.3 (1 – 1.6) 9.6 (4.6 – -65)
Costa Rica 58 (44 – 71) Likely increasing 1.1 (0.9 – 1.3) 27 (9 – -27)
Cote dIvoire 265 (235 – 292) Increasing 1.2 (1.1 – 1.3) 14 (9.1 – 29)
Croatia 5 (0 – 8) Likely increasing 2 (0.7 – 3.3) 3.5 (1.4 – -8)
Cuba 13 (5 – 19) Unsure 1 (0.6 – 1.4) -91 (6.2 – -5.4)
Czechia 54 (40 – 67) Unsure 1 (0.8 – 1.2) 230 (13 – -15)
Democratic Republic of the Congo 114 (95 – 130) Unsure 1 (0.9 – 1.1) -90 (25 – -16)
Denmark 43 (30 – 55) Unsure 1.1 (0.9 – 1.4) 24 (7.4 – -20)
Djibouti 27 (15 – 37) Decreasing 0.7 (0.4 – 0.9) -8.6 (-150 – -4.4)
Dominican Republic 482 (433 – 526) Increasing 1.1 (1 – 1.2) 39 (19 – -3100)
Ecuador 621 (562 – 680) Increasing 1.1 (1 – 1.2) 30 (17 – 110)
Egypt 1599 (1482 – 1707) Increasing 1.1 (1 – 1.1) 38 (25 – 83)
El Salvador 114 (94 – 130) Likely increasing 1.1 (1 – 1.2) 30 (12 – -50)
Equatorial Guinea 47 (33 – 60) Unsure 1.1 (0.8 – 1.3) -120 (11 – -9.5)
Estonia 7 (1 – 14) Unsure 0.9 (0.4 – 1.5) -12 (5.4 – -2.9)
Ethiopia 175 (152 – 200) Unsure 1.1 (0.9 – 1.2) 61 (16 – -35)
Finland 15 (6 – 23) Unsure 0.9 (0.6 – 1.2) -25 (8.8 – -5.2)
France 451 (407 – 494) Unsure 1 (0.9 – 1.1) 200 (31 – -46)
Gabon 136 (111 – 155) Increasing 1.3 (1.1 – 1.4) 10 (6.4 – 22)
Germany 325 (284 – 359) Unsure 1 (0.9 – 1.1) -490 (35 – -30)
Ghana 335 (291 – 373) Increasing 1.1 (1 – 1.2) 22 (13 – 81)
Greece 23 (14 – 32) Unsure 1.1 (0.8 – 1.4) 99 (7.5 – -9)
Guatemala 486 (430 – 545) Increasing 1.2 (1.1 – 1.3) 17 (12 – 32)
Guinea 69 (54 – 83) Likely increasing 1.1 (0.9 – 1.3) 24 (9.1 – -36)
Guinea Bissau 18 (9 – 26) Likely increasing 1.3 (0.9 – 1.7) 8.7 (3.8 – -28)
Haiti 145 (124 – 164) Unsure 1 (0.9 – 1.1) -48 (40 – -15)
Honduras 456 (401 – 509) Increasing 1.3 (1.1 – 1.4) 11 (8.2 – 17)
Hungary 12 (2 – 22) Unsure 1 (0.5 – 1.4) -39 (5.6 – -4.3)
Iceland 5 (0 – 9) Likely increasing 2.3 (0.6 – 4) 2.7 (1.2 – -5.8)
India 12344 (11458 – 13221) Increasing 1.1 (1.1 – 1.1) 26 (22 – 32)
Indonesia 1124 (1023 – 1224) Increasing 1.1 (1.1 – 1.2) 23 (16 – 40)
Iran 2595 (2390 – 2797) Increasing 1.1 (1 – 1.1) 49 (26 – 380)
Iraq 1358 (1218 – 1482) Increasing 1.2 (1.1 – 1.2) 23 (17 – 37)
Ireland 17 (8 – 23) Unsure 1 (0.6 – 1.3) 81 (6.5 – -7.9)
Israel 212 (177 – 242) Increasing 1.2 (1 – 1.3) 17 (10 – 55)
Italy 311 (274 – 348) Likely increasing 1.1 (1 – 1.1) 43 (18 – -100)
Japan 60 (44 – 73) Likely increasing 1.2 (1 – 1.4) 14 (6.8 – -130)
Kazakhstan 366 (320 – 414) Increasing 1.2 (1.1 – 1.3) 13 (9.1 – 22)
Kenya 151 (128 – 172) Likely increasing 1.1 (1 – 1.2) 33 (13 – -56)
Kosovo 40 (28 – 50) Likely increasing 1.3 (1 – 1.6) 11 (5.4 – -110)
Kuwait 562 (510 – 616) Likely decreasing 1 (0.9 – 1) -100 (72 – -29)
Kyrgyzstan 89 (72 – 106) Increasing 1.3 (1.1 – 1.5) 8.2 (5.3 – 19)
Latvia 4 (0 – 8) Unsure 1.4 (0.4 – 2.3) 7.5 (1.9 – -4)
Lebanon 17 (7 – 24) Unsure 1 (0.7 – 1.4) 380 (6.8 – -7.1)
Libya 18 (10 – 26) Unsure 0.9 (0.6 – 1.2) -24 (12 – -6)
Lithuania 8 (2 – 14) Unsure 1.1 (0.6 – 1.5) 440 (4.8 – -4.7)
Luxembourg 8 (2 – 13) Likely increasing 1.4 (0.7 – 2) 9 (2.8 – -7.3)
Madagascar 33 (20 – 43) Unsure 1 (0.7 – 1.2) -100 (11 – -9.2)
Malawi 18 (8 – 24) Unsure 1.1 (0.7 – 1.4) 24 (5.5 – -10)
Malaysia 25 (13 – 33) Likely decreasing 0.8 (0.5 – 1.1) -11 (22 – -4.4)
Maldives 26 (14 – 34) Unsure 1.1 (0.8 – 1.4) 15 (5.3 – -20)
Mali 32 (19 – 43) Unsure 0.9 (0.7 – 1.2) -43 (13 – -8.1)
Mauritania 135 (114 – 155) Increasing 1.2 (1 – 1.4) 13 (7.4 – 42)
Mexico 4756 (4427 – 5132) Increasing 1.1 (1.1 – 1.1) 29 (23 – 39)
Moldova 358 (311 – 396) Increasing 1.2 (1.1 – 1.3) 15 (10 – 28)
Mongolia 4 (0 – 7) Unsure 1.7 (0.3 – 3) 4.4 (1.4 – -3.7)
Morocco 78 (59 – 94) Unsure 1 (0.9 – 1.2) 340 (15 – -16)
Nepal 455 (418 – 492) Increasing 1.2 (1.1 – 1.3) 17 (12 – 33)
Netherlands 161 (137 – 185) Unsure 1 (0.9 – 1.1) -65 (36 – -17)
New Zealand 5 (0 – 10) Likely increasing 2.8 (0.4 – 5.3) 1 (0.8 – -3.7)
Niger 10 (3 – 15) Increasing 1.8 (0.9 – 2.7) 4.3 (2 – -53)
Nigeria 593 (527 – 647) Increasing 1.2 (1.1 – 1.2) 17 (12 – 30)
North Macedonia 159 (134 – 178) Likely increasing 1.1 (1 – 1.2) 35 (14 – -69)
Norway 17 (9 – 24) Unsure 1.1 (0.7 – 1.4) 75 (6.4 – -7.7)
Oman 1015 (946 – 1094) Increasing 1.1 (1.1 – 1.2) 25 (17 – 49)
Pakistan 5889 (5594 – 6249) Increasing 1.1 (1 – 1.1) 36 (27 – 53)
Palestine 20 (10 – 27) Increasing 1.7 (1.1 – 2.3) 4.5 (2.6 – 19)
Panama 713 (650 – 782) Increasing 1.2 (1.1 – 1.3) 17 (12 – 27)
Paraguay 17 (10 – 24) Unsure 0.9 (0.6 – 1.2) -23 (11 – -5.8)
Peru 4517 (4290 – 4726) Unsure 1 (1 – 1) 150 (63 – -460)
Philippines 542 (491 – 592) Unsure 1 (0.9 – 1.1) 960 (41 – -44)
Poland 422 (372 – 465) Unsure 1 (0.9 – 1.1) -170 (42 – -28)
Portugal 332 (284 – 368) Likely increasing 1 (1 – 1.1) 80 (22 – -50)
Puerto Rico 98 (79 – 115) Decreasing 0.9 (0.8 – 1) -17 (-390 – -8.9)
Qatar 1421 (1319 – 1506) Decreasing 1 (0.9 – 1) -77 (600 – -36)
Romania 280 (238 – 315) Increasing 1.2 (1.1 – 1.3) 14 (9.5 – 30)
Russia 8821 (8356 – 9396) Increasing 1 (1 – 1) 120 (66 – 950)
Saudi Arabia 4473 (4129 – 4878) Increasing 1.2 (1.1 – 1.2) 17 (14 – 20)
Senegal 103 (83 – 121) Unsure 1 (0.9 – 1.1) 940 (18 – -19)
Serbia 78 (59 – 93) Likely increasing 1.1 (0.9 – 1.2) 55 (12 – -22)
Sierra Leone 30 (18 – 40) Unsure 1.1 (0.8 – 1.4) 30 (7.2 – -14)
Singapore 319 (281 – 349) Likely decreasing 0.9 (0.9 – 1) -58 (78 – -21)
Slovakia 7 (1 – 11) Likely increasing 1.5 (0.6 – 2.4) 6.2 (2.2 – -8.1)
Somalia 35 (23 – 46) Unsure 0.9 (0.7 – 1.1) -30 (17 – -8)
South Africa 3714 (3431 – 4015) Increasing 1.2 (1.1 – 1.2) 17 (14 – 21)
South Korea 48 (36 – 61) Unsure 1.1 (0.9 – 1.3) 67 (10 – -15)
South Sudan 31 (18 – 41) Decreasing 0.8 (0.5 – 1) -8.4 (-57 – -4.5)
Spain 378 (332 – 415) Increasing 1.1 (1 – 1.2) 23 (13 – 75)
Sri Lanka 13 (5 – 19) Unsure 0.9 (0.5 – 1.3) -57 (5.9 – -4.8)
Sudan 221 (195 – 249) Increasing 1.1 (1 – 1.3) 19 (11 – 82)
Sweden 1164 (1065 – 1264) Increasing 1.1 (1 – 1.2) 25 (17 – 48)
Switzerland 25 (14 – 32) Likely increasing 1.2 (0.9 – 1.5) 17 (5.7 – -18)
Tajikistan 66 (51 – 81) Likely decreasing 0.9 (0.7 – 1.1) -29 (31 – -9.9)
Thailand 5 (0 – 8) Unsure 1.1 (0.4 – 1.9) 170 (3 – -3.2)
Tunisia 10 (4 – 17) Increasing 1.8 (0.9 – 2.7) 3.5 (1.8 – 43)
Turkey 1462 (1342 – 1604) Increasing 1.2 (1.1 – 1.2) 15 (12 – 20)
Uganda 13 (5 – 19) Likely decreasing 0.8 (0.5 – 1.2) -12 (11 – -3.9)
Ukraine 739 (667 – 815) Increasing 1.2 (1.1 – 1.3) 13 (9.9 – 19)
United Arab Emirates 427 (384 – 467) Decreasing 0.9 (0.8 – 1) -26 (-90 – -15)
United Kingdom 1340 (1241 – 1430) Unsure 1 (0.9 – 1) -190 (84 – -44)
United Republic of Tanzania 10 (3 – 15) Decreasing 0.7 (0.4 – 1) -8.7 (27 – -3.8)
United States of America 24861 (23167 – 26584) Increasing 1.1 (1.1 – 1.1) 33 (26 – 45)
Uzbekistan 154 (131 – 177) Increasing 1.1 (1 – 1.3) 25 (12 – -130)
Venezuela 101 (81 – 117) Unsure 1 (0.9 – 1.2) 3000 (17 – -17)
Yemen 55 (37 – 73) Increasing 1.3 (1 – 1.6) 9.3 (5 – 62)
Zambia 26 (14 – 36) Unsure 1.1 (0.8 – 1.3) 130 (8 – -9.2)
Zimbabwe 20 (11 – 27) Likely increasing 1.2 (0.8 – 1.6) 14 (4.8 – -15)